Tagamajig: Image Recognition via Crowdsourcing

The University of Tennessee, Knoxville (UTK) Library possesses thousands of unlabeled gray-scale photographs from the Smoky Mountains circa the 1920s - 1940s. Their current method of identifying and labeling attributes of the photographs is to do so manually. This is problematic both because of the scale of the collection as well as the reliance on an individual\u27s limited knowledge of the area\u27s numerous landmarks. In the past few years, similar dilemmas have been tackled via an approach known as crowd computing. Some examples include Floating Forests, in which users are asked to identify and mark kelp forests in satellite images, and Ancient Lives, which enlists users help in transcribing 2000-year-old manuscripts that Oxford University researchers had struggled to efficiently translate for over a century. For this particular problem, we propose releasing the image collections to the public through a web application. The application would target outdoor enthusiasts, conservationists, or professionals such as geologists, rangers, or historians who are familiar with the region and would find interest in helping to label the more recognizable photos. Users would tag landmarks using a hierarchically sorted data set of landmark names accessible via an incremental search. With sufficient participation, the image collection could be efficiently categorized and labeled beyond what is currently feasible using the librarys limited number of personnel. Furthermore, this application could easily be adapted to categorize other unlabeled image collections if provided with the proper data set for tagging

Effect of Chemoscan Creation on High School Students\u27 Attitudes Toward Science

Whether the activity of creating digital art influences high school students\u27 attitudes toward science is unknown. The purpose of this study was to determine if the creation of artistic digital chemoscans by high school students influences their attitudes toward science. In this study, ninth grade high school students\u27 attitudes toward science were examined after participating in the creation of chemoscans in their science classroom. The theory of affective domain helped explain the process that leads to a person\u27s behavior toward a certain phenomenon in the educational setting. The research questions concerned the use of chemoscan creation in the physical science classroom and if and whether implementation effected a change in students\u27 attitudes toward science. Archival pre- and posttest data from the Test of Science Related Attitude was used to measure high school students\u27 attitudes toward science in 7 categories. Archived student pre- and posttest data were treated with multiple regression for analysis. Key findings of this study showed that creation of artistic digital chemoscans (a) impacted one of the seven subscales of science attitude from the Test of Science related Attitude entitled attitude toward the normality of scientists, (b) did not have an impact on the any of the other six subscales from the TOSRA and (c) was influenced by teacher effect. This study may contribute to social change by providing improved training for science teachers who implement digital art activities, which may lead to some students enjoying science more and then possibly going into science careers